2024/05/13 by Markus Blut, Nancy V. Wünderlich, Christian Brock · 64 citations
Business, Management and Accounting · Computer Science · Decision Sciences · #AI in Service Interactions #Advertising #Business #Marketing #Sharing Economy and Platforms #Technology Adoption and User Behaviour
paper · doi:10.1016/j.jretai.2024.04.001
published in Journal of Retailing 100(2), 293-315 (Elsevier BV)
openalex publication_date 2024/05/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
Retailers rely on virtual assistants (VAs), such as Amazon's Alexa and chatbots, to deliver 24/7 customer service at low costs, as well as novel shopping opportunities. Despite improved VA capabilities due to artificial intelligence (AI), many retailers still struggle to convince customers to become repeat users of VAs. Therefore, to establish recommendations for how to facilitate VA use, this meta-analysis extracts 2,766 correlations from 244 independent samples of customers interacting with VAs. The results suggest that customer-, VA-, and shopping occasion–related factors all influence technology use. Price value is the strongest driver, followed by support, social influence, and anthropomorphism. Performance risk, competence, and trust matter to lesser extents. These factors exert strong indirect effects by triggering two customer responses: cognitive and emotional. Negative emotions emerge as a particularly important mediator. Finally, several VA types enhance or weaken the noted effects, including whether they are intelligent/less intelligent, commercial/noncommercial, voice-/text-based, and avatar-/non-avatar-based. The results suggest no one-size-fits-all approach applies for VAs, because their performance varies across customer responses. The current meta-analysis provides in-depth guidance for retailers seeking to select appealing VAs.